In some situations, there is a need to control multiple mobile agents according to a common objective. An agent can be any object capable to move in a controlled manner. Examples of the agents include mobile robots, UVs (Unmanned Vehicles), satellites, AUVs (Autonomous Underwater Vehicles), and solid particles in fluid flow. Each individual agent can move with prior dynamics, and its motion can be changed by control. All agents have same prior dynamics, and in a number of multi-agent control applications, such dynamic is non-linear.
Various multi-agent control applications aim to find control policies that move the agents to the desired states in an optimal manner. For example, one method computes individual optimal trajectories for all agents. However, this method is computationally expensive and does not scale when a number of agents is too high. Another method selects some agents as “leaders,” determines the trajectories only for the leaders and applies some leader-following algorithms for other agents. However, this method is sensitive to the failure of the leader agents. Yet another method determines trajectories of the agents by considering only linear dynamics of agents. However, the assumption of the linear dynamics is inaccurate in many cases.
Accordingly, there is a need for the multi-agent control system and method suitable for controlling the agents having non-linear dynamics.